class_docstr: Container for cluster load metrics.
  
  Metrics here are updated from raylet heartbeats. The autoscaler
  queries these metrics to determine when to scale up, and which nodes
  can be removed.
code: def set_resource_requests(self, requested_resources):
      if requested_resources is not None:
          assert isinstance(
              requested_resources, list
          ), requested_resources
      self.resource_requests = [
          request for request in requested_resources if len(request) > 0
      ]
  
imports: import logging
  import time
  from collections import Counter
  from functools import reduce
  from typing import Dict, List
  from ray._private.gcs_utils import PlacementGroupTableData
  from ray.autoscaler._private.constants import AUTOSCALER_MAX_RESOURCE_DEMAND_VECTOR_SIZE, AUTOSCALER_REPORT_PER_NODE_STATUS
  from ray.autoscaler._private.util import DictCount, LoadMetricsSummary, NodeIP, ResourceDict
  from ray.core.generated.common_pb2 import PlacementStrategy
label_desc: Use image node_id 16 for calling the LoadMetrics obj's underlying member method code with example usage: obj.set_resource_requests(requested_resources) without return types